1. Field of the Invention
The present invention relates to a method for recording a magnetic resonance image with a magnetic resonance device, of the type wherein several projection image data records are recorded (acquired) in succession with different gradient orientations, from which, through back projection, the magnetic resonance image is reconstructed.
2. Description of the Prior Art
In magnetic resonance imaging, different techniques are known for recording magnetic resonance images. One technique only recently proposed is the so-called SWIFT technique (Sweep Imaging with Fourier Transform). A description of this imaging technique can be found in the article of the same name by D. Idiyatullin et al., Proc. Intl. Soc. Mag. Reson. Med. 14 (2006) 2433 and also in U.S. Pat. Nos. 7,425,828 B2 and 7,403,006 B2.
The basic idea of the SWIFT technique is to record a number of projection data records of a type that, similar to computed tomography, can then be pieced together via the back projection method into the actual magnetic resonance image. In the SWIFT technique, the projection data records are recorded in different recording time frames that differ with respect to the gradient orientation. The duration of a time frame of each recording corresponds to the repetition time TR, and in each recording time frame, a frequency-modulated excitation pulse is used with an excitation duration that differs from the repetition time, essentially by the time required to achieve a new orientation of the magnetic field gradients for the coding of the spatial information in the next frame. During the excitation duration, a time-resolved reception signal is recorded (detected), from which the projection data record can be determined. The frequency modulated pulse, which can be divided into a series of pulse segments, each of which are separated by a pulse pause in which a readout process of the reception coil can be performed, thus ultimately serves the purpose of “covering” regions exhibiting differing resonance frequencies on the basis of the gradient. The excitation frequency is continuously, monotonically increasingly altered as to the excitation duration from a minimum value to a maximum value, so that nuclear spins in different “strips” can be sequentially excited with differing resonance frequencies.
Thereafter, the orientation of the gradients is altered and the method is repeated in order to obtain data for the next projection. After the time-resolved reception signal contains the results of all excitations, an expansion must be performed which, for example, can be a cross-correlation method that can be developed identically to the method of restoration of phase information in stochastic magnetic resonance. Finally, the calculation of the magnetic resonance image is implemented by means of back projection or by Radon transform. Characteristic here is the “sweep”, a continuous traversal of the regions in their physical sequence, which means the frequency modulation function is monotonically increasing or monotonically decreasing. In addition, an amplitude modulation is employed, using an amplitude modulation function that is the envelope in the case of the use of pulse segments. In the conventional, known process, a hyperbolic secant is proposed as the amplitude modulation function.
However, this known approach has a significant disadvantage with regard to the attainable image quality. With the use of a monotonically increasing frequency modulation function and a hyperbolic secant for the amplitude modulation, the pulse amplitude is greatest in the center of the image (projection data record). As a result, the image quality in the center strips is better than at the periphery. An additional disadvantageous effect is that the contrast (weighting) in the center of the image differs from the contrast at the periphery.
These disadvantages combine unfavorably with the properties of the image reconstruction, for example an inverse Radon transform, which produces a higher image quality in the center of the image than at the periphery of the image, since more data can be included in the calculation in the center and, as a result, the signal-noise ratio improves. This problem already has been known for some time, for example from computed tomography.